The recently published Intergovernmental Panel on Climate Change (IPCC) projections to 2100 give likely ranges of global temperature increase in four scenarios for population, economic growth and carbon use1. However these projections are not based on a fully statistical approach. Here we use a country-specific version of Kaya’s identity to develop a statistically-based probabilistic forecast of CO2 emissions and temperature change to 2100. Using data for 1960-2010, including the UN’s probabilistic population projections for all countries2–4, we develop a joint Bayesian hierarchical model for GDP per capita and carbon intensity. We find that the 90% interval for cumulative CO2 emissions includes the IPCC’s two middle scenarios but not the extreme ones. The likely range of global temperature increase is 2.0–4.9°C, with median 3.2°C and a 5% (1%) chance that it will be less than 2°C (1.5°C). Population growth is not a major contributing factor. Our model is not a “business as usual” scenario, but rather is based on data which already show the effect of emission mitigation policies. Achieving the goal of less than 1.5°C warming will require carbon intensity to decline much faster than in the recent past.

Disease, external stimuli (such as drugs and toxins), and mutations cause changes in the rate of protein synthesis, post-translational modification, inter-compartmental transport, and degradation of proteins in living systems. Recognizing and identifying the small number of proteins involved is complicated by the complexity of biological extracts and the fact that post-translational alterations of proteins can occur at many sites in multiple ways. It is shown here that a variety of new tools and methods based on internal standard technology are now being developed to code globally all peptides in control and experimental samples for quantification. The great advantage of these stable isotope-labeling strategies is that mass spectrometers can rapidly target those proteins that have changed in concentration for further analysis. When coupled to stable isotope quantification, targeting can be further focused through chromatographic selection of peptide classes on the basis of specific structural features. Targeting structural features is particularly useful when they are unique to types of regulation or disease. Differential displays of targeted peptides show that stimulus-specific markers are relatively easy to identify and will probably be diagnostically valuable tools.

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Introduced in the late 1980s as a reducing reagent, Tris (2-carboxyethyl) phosphine (TCEP) has now become one of the most widely used protein reductants. To date, only a few studies on its side reactions have been published. We report the observation of a side reaction that cleaves protein backbones under mild conditions by fracturing the cysteine residues, thus generating heterogeneous peptides containing different moieties from the fractured cysteine. The peptide products were analyzed by high performance liquid chromatography and tandem mass spectrometry (LC/MS/MS). Peptides with a primary amine and a carboxylic acid as termini were observed, and others were found to contain amidated or formamidated carboxy termini, or formylated or glyoxylic amino termini. Formamidation of the carboxy terminus and the formation of glyoxylic amino terminus were unexpected reactions since both involve breaking of carbon-carbon bonds in cysteine.

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This paper describes a heavy isotope coding strategy for the analysis of all types of tryptic peptides, including those that are N-terminally blocked and from the C-terminus of proteins. The method exploits differential derivatization of amine and carboxyl groups generated during proteolysis as a means of coding. Carboxyl groups produced during proteolysis incorporate 18O from H218O. Peptides from the C-terminus of proteins were not labeled with 18O unless they contained a basic C-terminal amino acid. Primary amines from control and experimental samples were differentially acylated after proteolysis with either 1H3- or 2H3-N-acetoxysuccinamide. When these two types of labeling were combined, unique coding patterns were achieved for peptides arising from the C-termini and blocked N-termini of proteins. This method was used to (1) distinguish C-terminal peptides in model proteins, (2) recognize N-terminal peptides from proteins in which the amino terminus is acylated, and (3) identify primary structure variations between proteins from different sources.

The Multi-Attribute Method (MAM) Consortium was initially formed as a venue to harmonize best practices, share experiences, and generate innovative methodologies to facilitate widespread integration of the MAM platform, which is an emerging ultra-high-performance liquid chromatography–mass spectrometry application. Successful implementation of MAM as a purity-indicating assay requires new peak detection (NPD) of potential process- and/or product-related impurities. The NPD interlaboratory study described herein was carried out by the MAM Consortium to report on the industry-wide performance of NPD using predigested samples of the NISTmAb Reference Material 8671. Results from 28 participating laboratories show that the NPD parameters being utilized across the industry are representative of high-resolution MS performance capabilities. Certain elements of NPD, including common sources of variability in the number of new peaks detected, that are critical to the performance of the purity function of MAM were identified in this study and are reported here as a means to further refine the methodology and accelerate adoption into manufacturer-specific protein therapeutic product life cycles.

In the phenylpropanoid production process, p-coumaric acid is the most important intermediate metabolite. It is generally accepted that the activity of tyrosine ammonia-lyase (TAL), which converts L-tyrosine to p-coumaric acid, represents the rate-limiting step. Therefore, an error-prone PCR-based random mutagenesis strategy was utilized for screening variants with higher catalytic activity. After rounds of screening, three variant enzymes were obtained, exhibiting improved production rates of 41.2, 37.1, and 38.0 %, respectively. Variants associated with increased expression level (S9N), improved catalytic efficiency (A11T), and enhanced affinity between TAL and L-tyrosine (E518V) were identified as beneficial amino acid substitutions by site-directed mutagenesis. Combining all of the beneficial amino acid substitutions, a variant, MT-S9N/-A11T/-E518V, exhibiting the highest catalytic activity was obtained. The K value of MT-S9N/-A11T/-E518V decreased by 25.4 % compare to that of wild-type, while the activity, k/K , and p-coumaric-acid yield were improved by 36.5, 31.2, and 65.9 %, respectively. Furthermore, the secondary structure of the 5'-end of MT-S9N mRNA and the three-dimensional protein structure of MT-E518V were modeled. Therefore, two potential mechanisms were speculated: (1) a simplified mRNA 5'-end secondary structure promotes TAL expression and (2) anchoring the flexible loop region (Glu325-Arg336) to maintain the active-site pocket opening ensures easy access by the L-tyrosine to the active site and thus improves p-coumaric acid yields.